Countries all around the world recognise the impact of air quality on public health, advocating for city centre decarbonisation and pollutant monitoring via Internet of Things technologies. Using data collected from these systems, it is possible to generate models that predict pollution based on regular patterns where mobility data can enhance the accuracy and robustness of these advanced machine learning models. This paper follows this approach, utilising vehicle traffic data from image recognition, on-site vehicle detectors, and synthetic data to maximise prediction accuracy in various urban environments. The results reveal that this proposal improves prediction for traffic-related pollutants, such as ${\text{SO}}_{2}$ and ${\text{PM}}_{2.5}$, which are linked to severe respiratory diseases. These results also highlight the role of synthetic data in enhancing prediction performance under limited datasets.

To support inter-vehicular applications, vehicles broadcast beacons with information about their state. Congestion may occur when the load on the channel due to beaconing can prevent the transmission of other types of messages. In this paper, we propose a distributed algorithm for optimal joint adaptation of transmit power and beaconing rate for congestion and awareness control. Our approach is based on a network utility formulation of the congestion control problem, which allows us to induce a desired fairness notion and set different priorities for vehicles. We formulate the general problem but, since it is not convex, we assume Rayleigh fading and derive an algorithm, called PRAIOS, that solves the optimization problem in a decentralized way with convergence guarantees. Our results, validated with realistic simulations in both static and dynamic scenarios and compared with other proposals, show that PRAIOS quickly converges to close to optimal allocations, while keeping the maximum beaconing load at the desired level. They also show that it can control the load when the fading is not Rayleigh. Applications can dynamically set their requirements as constraints, that are enforced by the algorithm while complying with the maximum load, which allows seamless integration of operational requirements into the control framework.

The importance of Hypertext Transfer Protocol (HTTP) in the interaction of users with the Internet is undisputed. Content Delivery Networks (CDNs) have emerged as a promising solution to enhance Quality of Service (QoS) provided in this type of transactions and to improve the network scalability. In this line, a new paradigm known as Information Centric Networks (ICNs) has been envisioned focusing the network routing on the content itself instead of attending to the topological addressing of nodes. A recent trend is using Software Define Networks (SDN) to manage data flows in this context. On top of an ICN as a Service (ICNaaS) architecture that provides end-to-end HTTP Information Centric Networking (ICN) alike transmissions with HTTP in-network caching, this paper proposes a dependable content aware prefetching mechanism, to enhance data transmission rates for first requesters that usually do not benefit from previous access to the same content. The validation tests have been conducted by considering the case of a video streaming service using the H.264/SVC codec with DASH. The obtained results corroborate the validity of the solution with cache hit ratios and client performance near to pre-cached content for video streaming.

Vehicular communications are bringing a new wave of applications under the umbrella of the Cooperative Intelligent Transportation Systems (C-ITS). To this end, on-board units are expected to send messages periodically or upon the appearance of a relevant event, to feed an awareness ecosystem that enables safety or traffic efficiency services. This is the case of Cooperative Awareness Messages (CAMs) in Europe, which contain basic vehicle information such as its position or speed, among other parameters. From a network security perspective, CAMs are broadcasted unencrypted over an unprotected radio channel, hence enabling their potential interception and the disclosure of sensitive data. Although public key infrastructures (PKI)-like solutions have been proposed, high computational cost of asymmetric cryptography to cipher application data remains a challenge and a confidentiality alternative is needed. In this work, we present the implementation and evaluation of a symmetric encryption scheme based on disjoint security domains distributed in geographical areas. In the solution, vehicles are able to coordinate and agree on common keys to be used in different security zones. Simulation results show the validity of the zone encryption scheme in diverse vehicular scenarios with different traffic densities. A potential issue in the zone key redistribution consisting in the propagation of wrongly-generated duplicated keys is also detected, which is discussed in detail and a reliable solution based on the support of third-party data-forwarders is proposed and tested. Evaluations reveal good performance of the zone encryption mechanism in terms of robustness and latency, guaranteeing the efficient access to a secured channel while maintaining low computing load.

The Internet of Things (IoT) has emerged as a key horizontal technology enabler within the 5G ecosystem, characterized by supporting the heterogeneity of end-devices, radio-access technologies, and services. Network slicing techniques allow to configure dedicated networks with assured resources to specific users or applications over a common physical infrastructure. This paper describes a novel end- to-end network slicing framework for IoT services in 5G systems, based on a Multi-Access Edge Computing (MEC) and central cloud architecture that permits the flexible and dynamic placement of micro-services encapsulated as Virtualized Network Functions (VNFs) along the end-to-end path. The critical analysis of the validation results highlights the performance and flexibility gains of our proposal. It allows deploying end-to-end slices over a number of participating domains in a very short time, it is able to isolate slices with guaranteed Quality of Service (QoS) parameters, and shows great scalability in terms of number of connected end-devices and application services.

Novel cooperative intelligent transportation systems (ITS) serve as the basis for the provision of a number of services for drivers, occupants, and third parties. The vast amount of information to be collected, especially in vehicle-to-infrastructure (V2I) communication services, requires new algorithms and hardware platforms to cope with real-time requirements; however, this combination is not properly addressed in the literature. In this paper, we introduce a high-throughput hardware-software infrastructure to gather information from vehicles and efficiently process it to provide novel ITS services. We propose a parallelization approach of a fuzzy clustering technique on heterogeneous servers based on CPU and several GPUs, tailored to classification problems in V2I. The infrastructure is empirically tested to offer a geo-located pollution information service through the periodical collection of both vehicle's position and status data. We offer a real service that correctly identifies highly polluting traffic areas and drivers. The results indicate a good performance of the system under high loads, and our scalability analysis reveals a good operation in real-ambitious deployments thanks to the use of the both CPU and multiple GPUs, showing that our proposal can efficiently host cooperative services involving high processing in the ITS context.

While satellite or cellular positioning implies dedicated hardware or network infrastructure functions, indoor navigation or novel IoT positioning techniques include flexible storage and computation requirements that can be fulfilled by both end‐devices or cloud back‐ends. Hybrid positioning systems support the integration of several algorithms and technologies; however, the common trend of delegating position calculation and storage of local geoinformation to mobile devices or centralized servers causes performance degradation in terms of delay, battery usage, and waste of network resources. The strategy followed in this work is offloading this computation effort onto the network edge, following a Mobile Edge Computing (MEC) approach. MEC nodes in the access network of the mobile device are in charge of receiving navigation data coming from both the smart infrastructure and mobile devices, in order to compute the final position following a hybrid approach. With the aim of supporting mobility and the access to multiple networks, an Information Centric Networking (ICN) solution is used to access generic position information resources. The presented system currently supports WiFi, Bluetooth LE, GPS, cellular and NFC technologies, involving both indoor and outdoor positioning, using fingerprinting and proximity for indoor navigation, and the integration of smart infrastructure data sources such as the door opening system within real smart campus deployment. Evaluations carried out reveal latency improvements of 50%, as compared with a regular configuration where position fixes are computed by mobile devices; at the same time the MEC solution offers extra flexibility features to manage positioning databases and algorithms and move extensive computation from constrained devices to the edge.

Communications will be a must for two-wheel vehicles integrated into future smart mobility environments. Two-wheelers will be connected with vehicular networks and smart cities, and for this to happen it is necessary not only a base technological support, but also a proper communication middleware able to maintain reachable the bike or moped through the network. In this work, we present a communication node for two-wheelers supporting network mobility and including 3G and 802.11p communication technologies. The communication unit has been designed and prototyped, and it has been provided with an IPv6 communication stack with an enhanced mobility management. The operation of the unit has been assessed in real environments, presenting good performance results and thus offering a novel platform suitable for the next generation of telematics services embracing two-wheelers.

A common practice is applying security after a network has been designed or developed. We have the opportunity of not committing this error in vehicular networks. Apart from particular works in the literature, ETSI TC ITS has defined general security services for (vehicular) cooperative systems. However, existent efforts do not pay the needed attention to the integration of IPv6 yet. The potential of IPv6 in the field is being described within ISO TC 204, above all, but further work is needed for a proper integration of security. This work follows this direction, and a reference vehicular communication architecture considering ETSI/ISO regulations, uses Internet Protocol security (IPsec) and Internet Key Exchange version 2 (IKEv2) to secure IPv6 Network Mobility (NEMO). A key advance is also the implementation and experimental evaluation of the proposal in a challenging vertical handover scenario between 3G and 802.11p. The performance of the secured NEMO channel is widely analyzed in terms of the movement speed, bandwidth, traffic type or signal quality, and it is concluded that the addition of IPv6 security only implies a slight reduction in the overall performance, with the great advantage of providing confidentiality, integrity and authenticity to the communication path.

Internet of Things (IoT) is a vision towards Future Internet where “things” are provided with enough intelligence to communicate with each other without the human intervention. In the near future, the number of IoT-enabled nodes is expected to grow substantially, therefore the heterogeneous nature of implementations demands effective IoT deployments that ensure proper interoperability and reliability of network infrastructures. In this line, we present a holistic IoT-based platform to gather and analyze information, and propose concrete actions according to different goals in smart environments. This platform bases on the optimal integration and use of data collected from a plethora of different sources. It has been deployed in a real IoT context framed in the smart buildings field. For its validation and evaluation, a reference scenario for indoor energy efficiency and comfort has been considered, where a set of tests have been carried out to validate the building management techniques implemented to maintain user comfort while assuring a good energy balance.

Vehicular communications attract the attention of many people in the networking research world. These networks present some special features, such as high mobility or specific topologies, which affect the performance of applications. In order to select the appropriate technologies, more effort should be directed to identify the final necessities of the network. Few works identify possible applications of vehicular networks, but none of them link application requirements which networking technologies available in the vehicular field. In this paper, we fill this gap, and propose an analysis of application requirements and study how to deal with them using communication technologies for the physical and network level. This study contains key factors which must be taken into account, especially, at the designing stage of the vehicular network.

Abstract — Nowadays, the growing demand on the implantation of onboard services for road vehicles encourages its development as a part of the current and future vehicles. In this sense, the implementation of new facilities cannot lead to an increase of hardware devices in the driver compartment, because space limitations and the need of an easy non-distracting interface with the user must be considered. For these reasons, it is advisable to have a service architecture suitable for further developments, considering the requirements of extensibility. New services should be created using modules shareable with the rest of applications in the vehicle. For this purpose, this work shows an extensible architecture useful in the software development of road services for vehicles. The solution presented is based on the division of services in different levels of abstraction, according to the underlying hardware. This structure is placed over a general purpose computer. A wide range of sensors has been installed in our test vehicle, allowing the implementation of several context aware services, and proving the feasibility of the proposed solution. A set of examples of location based services (LBS), multimedia services, and advanced driver assistance systems (ADAS) has been developed as described in this paper.

Nowadays, a new generation of civil location based services (LBS) included in the intelligent road transport systems (ITS-R) field is emerging. The reliability of positioning sensors and the communication infrastructure will be the key to the success of such services. A recommended basic onboard equipment (OBE) can include a GNSS based sensor, an embedded computer, a communication equipment and some other aiding sensors. The current GPS based sensors, operating in standard positioning service (SPS) or differential GPS (DGPS) modes, supply the level of accuracy required by many services of interest. However, the solution availability and the integrity monitoring are the main problems for GNSS based road applications, where the cost plays a significant role. In this paper, an embedded software for monitoring the availability and integrity of a GNSS positioning system is presented. The software developed allows the study of the HPLSBAS(Horizontal Protection Level) parameter as a reliable integrity indicator of the positioning system performance. Its suitability for road applications, and the importance of the geostationary satellite visibility and the GPRS/UMTS coverage are analyzed in this paper. Finally, selected results of these investigations and their conclusions are commented.